Yingying Zhu's portrait


Assistant Professor

Computer Science, University of Texas at Arlington

Arlington TX

Email: yingying dot zhu at uta dot edu


Google Scholar | Papers |Course


I am working in the Computer Science and Engineering Department, University of Texas at Arlington as an assistant professor and also a guest researcher working in clinical center, NIH. I was a Staff Scientist working with Ronald M. Summers at Clinical Center, National Institutes of Health. I work on the intersection of computer vision, medical image analysis, bioinformatics and machine learning with the goal of developing machine learning tools for solving real-world problems. I am currently looking for PhD student to working on machine learning, computer vision and medical data analysis. Details can be found here.

I did a postdoc at Cornell University working with Mert Sabuncu and postdoc in UNC Chapel Hill working with Guorong Wu. I obtained my Ph.D. from University of Queensland, Australia under the supervision of Simon Lucey (currently research associate professor in CMU, Pittsburgh, USA). I received my B.S. from Sichuan University and M. S. from University of Electronic Science and Technology of China.


Jan. 2022, Call for Paper: Frontiers in Digital Health: Pattern Recognition for Healthcare Analytics!


Jan. 2022, Served as Reviewer of MICCAI 2022!


Dec. 2021, One paper accepted by Medical Image Analysis!


Oct. 2021 One paper accepted by BMVC 2021!


Oct. 2021, One paper accepted by EMNLP 2021!


Sep. 2021, Served as Senior PC member of AAAI 2022!


July, 2021, We are organizing CVPR 2021 Tutorial on Medical Imaging Analysis!

Select Publications



Global-Local Attention Network with Multi-task Uncertainty Loss for Abnormal Lymph Node Detection in MR Images

Shuai Wang, Yingying Zhu, Sungwon Lee, Daniel C Elton, Thomas C Shen, Youbao Tang, Yifan Peng, Zhiyong Lu, Ronald M Summers

Medical Image Analysis 2022



Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data

Yifei Huan ,XiaoxiaoLi, linjin Yang, Lin Gu,Yingying Zhu, Hirofumi Seo, Qiuming Meng,Tatsuya Harada, Yoichi Sato




Automated Generation of Accurate \& Fluent Medical X-ray Reports

Hoang T.N. Nguyen, Dong Nie, Taivanbat Badamdorj, Yujie Liu, Yingying Zhu, Jason Truong, Li Cheng




Learning Structure from Visual Semantic Features and Radiology Ontology for Lymph Node Classification on MRI

Yingying Zhu, ShuaiWang, Qingyu Chen, Sungyong Lee, Thomas Shen, Daniel Elton, Zhiyong Lu, Ronald Summers

International Workshop on Machine Learning in Medical Imaging 2021



Source data‐free domain adaptation of object detector through domain‐specific perturbation

Lin Xiong, Mao Ye, Dan Zhang, Yan Gan, Xue Li, Yingying Zhu

International Journal of Intelligent Systems,2021



Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration

Qingyu Chen , Tiarnan D L Keenan , Alexis Allot , Yifan Peng , Elvira Agrón , Amitha Domalpally , Caroline C W Klaver , Daniel T Luttikhuizen , Marcus H Colyer , Catherine A Cukras , Henry E Wiley , M Teresa Magone , Chantal Cousineau-Krieger , Wai T Wong , Yingying Zhu , Emily Y Chew, Zhiyong Lu , AREDS2 Deep Learning Research Group

J Am Med Inform Assoc, 2021



COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature

Yifan Peng, Yuxing Tang, Sungwon Lee, Yingying Zhu, Ronald M. Summers, Zhiyong Lu

to appear in IEEE Transaction on Big Data 2020



Automatic recognition of abdominal lymph nodes from clinical text

Yifan Peng, Sungwon Lee, Shuai Wang, Qingyu Chen, Yingying Zhu, Ronald M. Summers, Zhiyong Lu

clinical NLP 2020



Atherosclerotic Plaque Burden on Abdominal CT: Automated Assessment with Deep Learning on Noncontrast and Contrast-enhanced Scans

Ronald M. Summers, Daniel C. Elton, Sungwon Lee, Yingying Zhu, Jiamin Liu , Mohammedhadi Bagheri, Veit Sandfort, Peter C. Grayson , Nehal N. Mehta, Peter A. Pinto, W. Marston Linehan, Alberto A. Perez , Peter M. Graffy , Stacy D. O’Connor, Perry J. Pickhardt

Academic Radiology, 2020



An Interpretable Generative Model for Abnormal Disease Separation and Radiorealistic Normal ChestX-ray Synthesis

Youbao Tang, Yuxing Tang, Yingying Zhu, Jing Xiao, Ronald M. Summers

to appear in Medical Image Analysis 2020



Cross-Domain Medical Imaging Translation using Shared Gaussian Mixture Model

Yingying Zhu, Youbao Tang, Yuxing Tang, Daniel C. Elton, Sungwon Lee, Perry J. Pickhardt, Ronald M. Summers




E2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans

Youbao Tang, Yuxing Tang, Yingying Zhu, Ronald M. Summers

Early Accepted by MICCAI 2020



Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Segmentations

Yingying Zhu, Daniel C. Elton, Sungwon Lee, Perry J. Pickhardt, Ronald M. Summers

Medical Imaging with Deep Learning (MIDL) 2020



Long Range Early Diagnosis of Alzheimer's Disease Using Longitudinal MR Imaging Data

Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Guorong Wu

to appear in Medical Image Analysis 2020



Detecting Cannabis-Associated Cognitive Impairment Using Resting-State fNIRS

Yingying Zhu, Jodi Gilman, Anne Eden Evins, Mert Sabuncu

MICCAI 2019, oral presentation, accept rate<5%



A Bayesian Disease Progression Model for Clinical Trajectories

Yingying Zhu, Mert Sabuncu

GRAIL 2018, Beyond MIC 2018, oral presentation



Dynamic fMRI networks predict success in a behavioral weight loss program among older adults

Fatemeh Mokhtari, W Jack Rejeski, Yingying Zhu, Guorong Wu, Sean L Simpson, Jonathan H Burdette, Paul J Laurienti

Neuroimage 2018



Dynamic Hyper-Graph Inference Framework for Computer-Assisted Diagnosis of Neurodegenerative Diseases

Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Daniel Kaufer, Guorong Wu

IEEE transactions on medical imaging 38 (2), 608-616, 2018



A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome

Yingying Zhu, Mert R Sabuncu

arXiv preprint arXiv:1803.05011 2018



Personalized diagnosis for Alzheimer's disease

Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Jin Yan, Daniel Kaufer and Guorong Wu




Multi-modal classification of neurodegenerative disease by progressive graph-based transductive learning

Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Feiping Nie, Brent Munsell, Guorong Wu

Medical Image Analysis 2017



A tensor statistical model for quantifying dynamic functional connectivity

Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Guorong Wu

IPMI 2017



A novel dynamic hyper-graph inference framework for computer assisted diagnosis of neuro-diseases

Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Guorong Wu

IPMI 2017



Progressive graph-based transductive learning for multi-modal classification of brain disorder disease

Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Chen Zu, Feiping Nie, Dinggang Shen, Guorong Wu




Reveal consistent spatial-temporal patterns from dynamic functional connectivity for autism spectrum disorder identification

Yingying Zhu, Xiaofeng Zhu, Han Zhang, Wei Gao, Dinggang Shen, Guorong Wu




Early diagnosis of Alzheimer's disease by joint feature selection and classification on temporally structured support vector machine

Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Dinggang Shen, Guorong Wu

MICCAI 2016, oral presentation, accept rate < 5%



Complex non-rigid motion 3d reconstruction by union of subspaces

Yingying Zhu, Dong Huang, Fernando De La Torre, Simon Lucey

CVPR 2014



Convolutional sparse coding for trajectory reconstruction

Yingying Zhu, Simon Lucey

IEEE transactions on pattern analysis and machine intelligence 2014



Efficient Articulated Trajectory Reconstruction Using Dynamic Programming and Filters

Jack Valmadre, Yingying Zhu, Sridha Sridharan, Simon Lucey

ECCV 2012



3D motion reconstruction for real-world camera motion

Yingying Zhu, Mark Cox, Simon Lucey

CVPR 2011





CSE 5368 Neural Networks Fall 2020

Syllabus CSE-5368-002


CSE 6363 Machine Learning Spring 2022 and Fall 2021

Syllabus CSE-6363